Under-screen fingerprint sensing device and fingerprint sensing method

ABSTRACT

An under-screen fingerprint sensing device and a fingerprint sensing method are provided. The under-screen fingerprint sensing device includes a fingerprint sensor and a processor. The processor performs FFC on the multiple first color original values, multiple second color original values, and multiple third color original values provided by the fingerprint sensor, respectively, to generate multiple first color correction values, multiple second color correction values and multiple third color correction values. The processor inputs the first color correction values, the second color correction values, and the third color correction values to a determining module to determine whether the target object is a real finger.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the priority benefit of U.S. application Ser.No. 63/155,742, filed on Mar. 3, 2021, and China application serial no.202210028086.3, filed on Jan. 11, 2022. The entirety of each of theabove-mentioned patent applications is hereby incorporated by referenceherein and made a part of this specification.

BACKGROUND Technical Field

The present disclosure relates to a biometric sensing technology, andmore particularly, to an under-screen fingerprint sensing device and afingerprint sensing method.

Description of Related Art

Currently, fingerprint sensing technology has been applied in variouselectronic devices to provide an identity recognition function forsecurity. However, when others use fake fingerprints for fingerprintsensing, the current fingerprint sensing technology is unable toeffectively differentiate the real finger from the fake finger. Inaddition, in the process of fingerprint sensing, when the sensingenvironment changes, the current fingerprint sensing technology is alsoeasily affected by the change of the sensing environment, which makes itimpossible to correctly differentiate the real finger from the fakefinger.

SUMMARY

In view of this, the present disclosure provides an under-screenfingerprint sensing device and a fingerprint sensing method, which caneffectively determine whether the target object for fingerprint sensingis a real finger.

The under-screen fingerprint sensing device of the present disclosure isadaptable for electronic equipment with a display device. Theunder-screen fingerprint sensing device includes a fingerprint sensorand a processor. The fingerprint sensor is arranged below the displaydevice. The fingerprint sensor has a pixel array. A plurality of pixelgroups of the pixel array have a plurality of first color pixels, aplurality of second color pixels, and a plurality of third color pixels.When the fingerprint sensor senses the target object, the first colorpixels, the second color pixels and the third color pixels of the pixelgroups output a plurality of first color original values, a plurality ofsecond color original values and a plurality of third color originalvalues respectively. The processor is coupled to the pixel array. Theprocessor performs flat-filed correction (FFC) on the first colororiginal values, the second color original values and the third colororiginal values, respectively, to generate a plurality of first colorcorrection values, a plurality of second color correction values and aplurality of third color correction values. The processor inputs thefirst color correction values, the second color correction values andthe third color correction values into a determining module so as to becompared with at least one of a first database and a second database, todetermine whether the target object is a real finger.

The fingerprint sensing method of the present disclosure includes thefollowing steps. When the fingerprint sensor senses the target object,the plurality of first color pixels, the plurality of second colorpixels and the plurality of third color pixels of the plurality of pixelgroups of the pixel array of the fingerprint sensor output the pluralityof first color original values, the plurality of second color originalvalues and the plurality of third color original values, respectively.The first color original values, the second color original values andthe third color original values are respectively subjected to FFC togenerate the plurality of first color correction values, the pluralityof second color correction values and the plurality of third colorcorrection values. The first color correction values, the second colorcorrection values and the third color correction values are input to thedetermining module so as to be compared with at least one of the firstdatabase and the second database, to determine whether the target objectis a real finger.

Based on the above, the under-screen fingerprint sensing device and thefingerprint sensing method of the present disclosure can perform FFC onthe color original values of different colors obtained by thefingerprint sensor, so as to effectively determine whether the targetobject is a real finger according to the corrected values.

In order to make the above-mentioned features and advantages of thepresent disclosure more comprehensible, the following examples are givenand described in detail with the accompanying drawings as follows.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic circuit diagram of an under-screen fingerprintsensing device according to an embodiment of the present disclosure.

FIG. 2 is a schematic diagram of a pixel array according to anembodiment of the present disclosure.

FIG. 3 is a flowchart of the fingerprint sensing method according to thefirst embodiment of the present disclosure.

FIG. 4 is a flowchart of determining the sensing environment accordingto the first embodiment of the present disclosure.

FIG. 5 is a schematic circuit diagram of an under-screen fingerprintsensing device according to another embodiment of the presentdisclosure.

FIG. 6 is a flowchart of a fingerprint sensing method according to asecond embodiment of the present disclosure.

FIG. 7 is a flowchart of a fingerprint sensing method according to athird embodiment of the present disclosure.

FIG. 8 is a flowchart of a fingerprint sensing method according to afourth embodiment of the present disclosure.

DESCRIPTION OF THE EMBODIMENTS

In order to make the content of the present disclosure morecomprehensible, the following specific embodiments are taken as examplesby which the present disclosure can indeed be implemented. Additionally,where possible, elements/components/steps using the same referencenumerals in the drawings and embodiments represent the same or similarparts.

FIG. 1 is a schematic circuit diagram of an under-screen fingerprintsensing device according to an embodiment of the present disclosure.FIG. 2 is a schematic diagram of a pixel array according to anembodiment of the present disclosure. Referring to FIG. 1 and FIG. 2,the under-screen fingerprint sensing device 100 includes a processor110, a fingerprint sensor 120 and a storage device 130. The processor110 is coupled to the fingerprint sensor 120 and the storage device 130.In this embodiment, the under-screen fingerprint sensing device 100 isadaptable for an electronic device (or terminal device) having a displaydevice. The fingerprint sensor 120 may be an optical fingerprint sensor.The fingerprint sensor 120 can be disposed under the display device, andcan be used to sense a target object located above the display device.When the under-screen fingerprint sensing device 100 performsfingerprint sensing, the display device of the electronic device orother light source elements disposed under the screen can provideillumination light to the target object, so that the fingerprint sensor120 can receive the sensing light reflected by the surface (that is, thefinger surface) of the target object to generate a fingerprint image.

In this embodiment, the under-screen fingerprint sensing device 100 canbe a fingerprint sensing module, and the fingerprint sensing module isintegrated in an electronic device with a display device, and theelectronic device is, for example, a smart phone. However, the presentdisclosure is not limited thereto. The processor 110 and the storagedevice 130 can be a processing chip and a memory provided in thefingerprint sensing module, and can provide the fingerprint image andthe determining result of whether the target object is a real finger tothe central processing unit of the electronic device, so that thecentral processing unit of the electronic device performs othersubsequent functions or operations according to the fingerprint imageand the determining result of whether the target object is a realfinger. Alternatively, in an embodiment, the processor 110 may be aprocessing chip provided in the fingerprint sensing module, and thestorage device 130 may be provided in the electronic device.Alternatively, in another embodiment, the under-screen fingerprintsensing device 100 may refer to an electronic device itself with afingerprint sensing function, and the processor 110 and the storagedevice 130 may be the central processing unit (or graphics processingunit) and memory of the electronic device.

In this embodiment, as shown in FIG. 2, the fingerprint sensor 120 mayinclude a pixel array 200. The pixel array 200 includes a plurality ofpixels 210_1 to 210_M, and M is a positive integer. It should be notedthat at least a part of the pixel array 200 can be divided into aplurality of pixel groups 211_1 to 211_N, and N is a positive integer.In this embodiment, the plurality of pixel groups 211_1 to 211_N mayinclude a first color pixel 211R_1 to 211R_N, a second color pixel211G_1 to 211G_N, and a third color pixel 211B_1 to 211B_N,respectively. In an embodiment, the first color pixel 211R_1 to 211R_N,the second color pixel 211G_1 to 211G_N and the third color pixel 211B_1to 211B_N respectively include a red color filter, a green filter and ablue filter formed on the light incident surface of various pixels. Inthis aspect, the first color pixel 211R_1 to 211R_N, the second colorpixel 211G_1 to 211G_N, and the third color pixel 211B_1 to 211B_N maybe red sensing pixels (R), green sensing pixels (G), and blue sensingpixels (B), respectively.

In this embodiment, when the under-screen fingerprint sensing device 100performs fingerprint sensing, for example, the first color pixel 211R_1,the second color pixel 211G_1 and the third color pixel 211B_1 canrespectively output the sensing results (analog data) to the analog todigital converter (ADC), so that the ADC can output a plurality ofcorresponding ADC codes (digital data) to the processor 110 as the firstcolor original value (raw data), second color original value, and thirdcolor original value. The aforementioned ADC may be provided in theprocessor 110 or the fingerprint sensor 120. In this embodiment, thestorage device 130 may store, for example, the first flatteningalgorithm and/or the second flattening algorithm. The processor 110 mayexecute the first flattening algorithm and/or the second flatteningalgorithm to perform a first flat-filed correction (FFC) and/or a secondFFC on the obtained first color original value, second color originalvalue and third color original value.

In this embodiment, the first FFC means that the processor 110 canperform the first FFC on the obtained first color original value (R1),the second color original value (G1) and the third color original value(B1) according to the pre-stored first low reference value(corresponding to the red low reference value Rb), the second lowreference value (corresponding to the green low reference value Gb), thethird low reference value (corresponding to the blue low reference valueBb), the first high reference value (corresponding to the red highreference value Rs), the second high reference value (corresponding tothe green high reference value Gs) and the third high reference value(corresponding to the blue high reference value Bs). In this embodiment,the first low reference value (Rb), the second low reference value (Gb),and the third low reference value (Bb) are three ADC values respectivelycorresponding to the first color, the second color and the third colorand generated after the fingerprint sensor 120 (for example, beforeshipping from the factory) senses a standard black object (for example:black rubber block) once, or three average ADC values respectivelycorresponding to the first color, the second color, and the third colorand generated after the fingerprint sensor 120 senses the standard blackobject (for example: black rubber block) for multiple times. The firsthigh reference value (Rs), the second high reference value (Gs), and thethird high reference value (Bs) can be three ADC values respectivelycorresponding to the first color, the second color and the third colorgenerated and generated after the fingerprint sensor 120 (e.g., thefingerprint sensing result performed after shipping from the factory)senses a standard skin-colored object (e.g., skin-colored rubber block)once, or three average ADC values respectively corresponding to thefirst color, the second color, and the third color and generated afterthe fingerprint sensor 120 senses the standard skin-colored object(e.g., skin-colored rubber block) for multiple times.

In this embodiment, the processor 110 can execute the following formula(1) to formula (3) to perform the first FFC, so that the processor 110can obtain the first color correction value (FFC1_R1), the second colorcorrection value (FFC1_G1) and the third color correction value(FFC1_B1). In this embodiment, the processor 110 performs subtractioncalculation on the first color original value (R1) and the first lowreference value (Rb) to obtain the first calculation value, and theprocessor 110 performs subtraction calculation on the first highreference value (Rs) and the first low reference value (Rb) to obtainthe second calculation value. The processor 110 divides the firstcalculation value by the second calculation value to obtain the firstcolor correction value (FFC1_R1). The processor 110 performs subtractioncalculation on the second color original value (G1) and the second lowreference value (Rb) to obtain a third calculation value, and theprocessor 110 performs subtraction calculation on the second highreference value (Gs) and the second low reference value (Gb) to obtainthe fourth calculation value. The processor 110 divides the thirdcalculation value by the fourth calculation value to obtain the secondcolor correction value (FFC1_G1). The processor 110 performs subtractioncalculation on the third color original value (B1) and the third lowreference value (Gb) to obtain the fifth calculation value, and theprocessor 110 performs subtraction calculation on the third highreference value (Bs) and the third low reference value (Bb) to obtainthe sixth calculation value. The processor 110 divides the fifthcalculation value by the sixth calculation value to obtain the thirdcolor correction value (FFC1_B1).

$\begin{matrix}{\frac{{R1} - {Rb}}{{Rs} - {Rb}} = {{FFC1\_ R}1}} & {{Equation}(1)} \\{\frac{{G1} - {Gb}}{{Gs} - {Gb}} = {FFC1\_ G1}} & {{Equation}(2)} \\{\frac{{B1} - {Bb}}{{Bs} - {Bb}} = {FFC1\_ B1}} & {{Equation}(3)}\end{matrix}$

In this embodiment, the second FFC means that the processor 110 canperform the second FFC on the obtained first color original value (R1),the second color original value (G1) and the third color original value(B1) according to the pre-stored first low reference value(corresponding to the red low reference value Rb), the second lowreference value (corresponding to the green low reference value Gb), thethird low reference value (corresponding to the blue low reference valueBb), another first high reference value (corresponding to the red highreference value Rw), another second high reference value (correspondingto the green high reference value Gw) and another third high referencevalue (corresponding to the blue high reference value Bw). In thisembodiment, the first low reference value (Rb), the second low referencevalue (Gb), and the third low reference value (Bb) are three ADC valuesrespectively corresponding to the first color, the second color and thethird color and generated after the fingerprint sensor 120 (for example,before shipping from the factory) senses a standard black object. Thefirst high reference value (Rw), the second high reference value (Gw),and the third high reference value (Bw) can be three ADC valuesrespectively corresponding to the first color, the second color, and thethird color and generated after the fingerprint sensor 120 (for example,before shipping from the factory) senses a standard white object once orthree average ADC values obtained from sensing the standard white objectmultiple times.

In this embodiment, the processor 110 can execute the followingequations (4) to (6) to perform the second FFC, so that the processor110 can obtain another first color correction value (FFC2_R1), anothersecond color correction value (FFC2_G1) and another third colorcorrection value (FFC2_B1). The detailed descriptions for calculationexpressed in the following equations (4) to (6) can be deduced byreferring to the descriptions of the above equations (1) to (3), andthus are not repeated here.

$\begin{matrix}{\frac{{R1} - {Rb}}{{Rw} - {Rb}} = {{FFC2\_ R}1}} & {{Equation}(4)} \\{\frac{{G1} - {Gb}}{{Gw} - {Gb}} = {FFC2\_ G1}} & {{Equation}(5)} \\{\frac{{B1} - {Bb}}{{Bw} - {Bb}} = {FFC2\_ B1}} & {{Equation}(6)}\end{matrix}$

In addition, it should be noted that the anti-counterfeiting operationin the following embodiments can be carried out with the numeralanalysis and calculation described in the following embodiments based onthe sensing results of the respective first color pixel, second colorpixel and third color pixel of the plurality of pixel groups 211_1 to211_N in the pixel array 200. In addition, the processor 110 may countthe plurality of determining results of the pixel groups 211_1 to 211_N,and determine the final determining result of the real and fake fingersaccording to the counting results. For example, if P groups in the pixelgroups 211_1 to 211_N determine that the target object is real finger,and if P is greater than a preset threshold, the processor 110determines that the target object is a real finger. On the contrary, ifP is less than or equal to the preset threshold, the processor 110determines that the target object is a fake finger. The numericalanalysis and calculations in the following embodiments are describedbased on the sensing results of the first color pixel, the second colorpixel, and the third color pixel of a single pixel group, and can beanalogized to the numerical analysis and calculations of multiple pixelgroups 211_1 to 211_N.

FIG. 3 is a flowchart of the fingerprint sensing method according to thefirst embodiment of the present disclosure. Referring to FIG. 1 to FIG.3, the under-screen fingerprint sensing device 100 can perform thefollowing steps S310 to S350 to realize the anti-counterfeitingfunction. In this embodiment, the under-screen fingerprint sensingdevice 100 executes steps S310 to S350. In step S310, the under-screenfingerprint sensing device 100 can sense the target object through thefingerprint sensor 120, so that the first color pixel 211R_1, the secondcolor pixel 211G_1 and the third color pixel 211B_1 of the pixel array200 of the fingerprint sensor 120 output the first color original value(R1), the second color original value (G1), and the third color originalvalue (B1) respectively. In step S320, the processor 110 may perform FFCon the first color original value (R1), the second color original value(G1), and the third color original value (B1), respectively, to generatethe first color correction value, the second color correction value, andthe third color correction value. It is worth noting that, in thisembodiment, the processor 110 may perform the aforementioned first FFCor second FFC on the first color original value (R1), the second colororiginal value (G1), and the third color original value (B1),respectively. Alternatively, the processor 110 may simultaneouslyperform the aforementioned first FFC and second FFC on the first colororiginal value (R1), the second color original value (G1), and the thirdcolor original value (B1), respectively, so as to make judgment with thefollowing preset conditions based on the numerical result of two FFCs.In step S330, the processor 110 may determine whether the first colorcorrection value, the second color correction value and the third colorcorrection value satisfy a preset condition. If not, in step S350, theprocessor 110 determines that the target object is a fake finger, so asto stop using the current fingerprint image for subsequent fingerprintanalysis. If yes, in step S340, the processor 110 determines that thetarget object is a real finger. Therefore, the under-screen fingerprintsensing device 100 and the fingerprint sensing method of the presentembodiment can realize the function of judging whether the target objectis a real finger.

In this embodiment, the preset condition may, for example, refer to thefirst numerical analysis method described below. The first numericalanalysis method may refer to the processor 110 determining whether thevalues obtained through dividing the first color correction value by thesecond color correction value, dividing the second color correctionvalue by the third color correction value, and dividing the first colorcorrection value by the third color correction are greater than thefirst threshold and less than the second threshold, respectively.

Take the processor 110 performing the aforementioned first FFC on thefirst color original value (R1), the second color original value (G1),and the third color original value (B1) as an example. The processor 110may make judgment through the following equations (7) to (9) on thefirst color correction value (FFC1_R1), the second color correctionvalue (FFC1_G1) and the third color correction value (FFC1_B1) processedafter the first FFC, to judge whether the target object is a fake fingeror a real finger. In this aspect, if equation (7) to equation (9) areall satisfied, the target object is determined to be a real finger. Ifat least one of equation (7) to equation (9) is not satisfied, it isdetermined that the target object is a fake finger. The parameter TH1 isthe first threshold. The parameter TH2 is the second threshold. In anembodiment, the parameter TH1 may be 0.8, and the parameter TH2 may be1.2.

$\begin{matrix}{{{TH}1} < \frac{FFC1\_ R1}{FFC1\_ G1} < {{TH}2}} & {{Equation}(7)} \\{{{TH}1} < \frac{FFC1\_ G1}{FFC1\_ B1} < {{TH}2}} & {{Equation}(8)} \\{{{TH}1} < \frac{FFC1\_ R1}{FFC1\_ B1} < {{TH}2}} & {{Equation}(9)}\end{matrix}$

Take the processor 110 performing the aforementioned second FFC on thefirst color original value (R1), the second color original value (G1),and the third color original value (B1) as an example. The processor 110may make judgment through the following equations (10) to (12) on thefirst color correction value (FFC2_R1), the second color correctionvalue (FFC2_G1) and the third color correction value (FFC2_B1) processedafter the second FFC, to judge whether the target object is a fakefinger or a real finger. In this aspect, if equation (10) to equation(12) are all satisfied, the target object is determined to be a realfinger. If at least one of the equation (10) to the equation (12) is notsatisfied, it is determined that the target object is a fake finger.

$\begin{matrix}{{{TH}1} < \frac{FFC2\_ R1}{FFC2\_ G1} < {{TH}2}} & {{Equation}(10)} \\{{{TH}1} < \frac{FFC2\_ G1}{FFC2\_ B1} < {{TH}2}} & {{Equation}(11)} \\{{{TH}1} < \frac{FFC2\_ R1}{FFC2\_ B1} < {{TH}2}} & {{Equation}(12)}\end{matrix}$

In an embodiment, the preset condition may, for example, refer to thesecond numerical analysis method described below. The second numericalanalysis method may refer to that the under-screen fingerprint sensingdevice 100 can continuously sense the target object twice through thefingerprint sensor 120, so that the first color pixel 211R_1, the secondcolor pixel 211G_1 and the third color pixel 211B_1 of the pixel arrayof the fingerprint sensor 120 respectively output the first colororiginal value (R1), the second color original value (G1) and the thirdcolor original value (B1) corresponding to the first sensing operation(acquiring the first image), and another first color original value(R1′), another second color original value (G1′), and another thirdcolor original value (B1′) corresponding to the second sensing operation(acquiring the second image). The processor 110 may perform the same FFC(e.g., the first FFC and/or the second FFC) on the first color originalvalue (R1), the second color original value (G1), the third colororiginal value (B1), another first color original value, another secondcolor original value, and another third color original valuerespectively, to generate a first color correction value, a second colorcorrection value, a third color correction value, another first colorcorrection value, another second color correction value, and anotherthird color correction value. Next, the processor 110 may determinewhether a first difference between the first color correction value andanother first color correction value, a second difference between thesecond color correction value and another second color correction value,and a third difference between the third color correction value andanother third color correction value are respectively greater than 0. Ifnot, in step S350, the processor 110 determines that the target objectis a fake finger, so as to stop using the current two fingerprint imagesfor subsequent fingerprint analysis. If yes, in step S340, the processor110 determines that the target object is a real finger, and theprocessor 110 or the central processing unit of the electronic devicecan perform subsequent fingerprint analysis on at least one of the twocurrent fingerprint images. Therefore, the under-screen fingerprintsensing device 100 and the fingerprint sensing method of the presentembodiment can realize the function of judging whether the target objectis a real finger.

It is exemplified in the following that the processor 110 performs theaforementioned first FFC on the first color original value (R1), thesecond color original value (G1) and the third color original value (B1)of the first fingerprint image, respectively, and performs the first FFCon the first color original value (R1′), the second color original value(G1′), and the third color original value (B1′) of the secondfingerprint image respectively. The processor 110 can make judgment onthe first color correction value (FFC1_R1), the second color correctionvalue (FFC1_G1), the third color correction value (FFC1_B1) of the firstfingerprint image after being processed with the first FFC, as well asthe first color correction value (FFC1_R1′), the second color correctionvalue (FFC1_G1′), and the third color correction value (FFC1_B1′) of thesecond fingerprint image after being processed with the first FFCexpressed in the following equation (13) to equation (15), to determinewhether the target object is a fake finger or a real finger. In thisaspect, if equation (13) to equation (15) are all satisfied, the targetobject is determined to be a real finger. If at least one of theequation (13) to the equation (15) is not satisfied, it is determinedthat the target object is a fake finger.

FFC1_R1−FFC1_R1′>0  Equation (13)

FFC1_G1−FFC1_G1′>0  Equation (14)

FFC1_B1−FFC1_B1′>0  Equation (15)

It is exemplified in the following that the processor 110 performs theaforementioned second FFC on the first color original value (R1), thesecond color original value (G1) and the third color original value (B1)of the first fingerprint image, respectively, and performs the secondFFC on the first color original value (R1′), the second color originalvalue (G1′), and the third color original value (B1′) of the secondfingerprint image respectively. The processor 110 can make judgment onthe first color correction value (FFC2_R1), the second color correctionvalue (FFC2_G1), the third color correction value (FFC2_B1) of the firstfingerprint image after being processed with the second FFC, as well asthe first color correction value (FFC2_R1′), the second color correctionvalue (FFC2_G1′), and the third color correction value (FFC2_B1′) of thesecond fingerprint image after being processed with the second FFCexpressed in the following equation (16) to equation (18), to determinewhether the target object is a fake finger or a real finger. In thisaspect, if equation (16) to equation (18) are all satisfied, the targetobject is determined to be a real finger. If at least one of theequation (16) to the equation (18) is not satisfied, it is determinedthat the target object is a fake finger.

FFC2_R1−FFC2_R1′>0  Equation (16)

FFC2_G1−FFC2_G1′>0  Equation (17)

FFC2_B1−FFC2_B1′>0  Equation (18)

It is worth noting that, in other embodiments, the processor 110 mayalso first perform the above-mentioned judgment through the firstnumerical analysis method, and if the determining result is “No”, thenthe above-mentioned second numerical analysis method is executed to makejudgment. Alternatively, the processor 110 may also first make thejudgment through the second numerical analysis method described above,and if the determining result is “No”, then the first numerical analysismethod described above is executed to make judgment.

In addition, in other embodiments of the present disclosure, theprocessor 110 may further perform the above numeral analysis andcalculation on the sensing results of the respective first color pixel,second color pixel and third color pixel of the pixel groups 211_1 to211_N in the pixel array 200, and perform statistical calculation on theplurality of determining results of the pixel groups 211_1 to 211_N. Inthis respect, when the multiple determining results of the pixel groups211_1 to 211_N are that the number of real fingers is greater than thefirst predetermined determining threshold, the final determining resultis output as that the target object is a real finger. On the contrary,the output final determining result is that the target object is a fakefinger.

FIG. 4 is a flowchart of determining the sensing environment accordingto the first embodiment of the present disclosure. Referring to FIG. 1and FIG. 4, in other embodiments of the present disclosure, theunder-screen fingerprint sensing device 100 may further determinewhether the confirmation result of the current sensing environment is anexception after it is determined “No” in the above-mentioned step S330(that is, steps S310 to S330 and S410 to 440 can be executed insequence) (based on the numerical result of the first FFC), so that theprocessor 110 or the central processing unit of the electronic devicestill performs subsequent fingerprint analysis on the currentfingerprint image. In step S410, the processor 110 may determine whetherthe current sensing environment is a strong light environment. In thisaspect, the processor 110 may first perform the first FFC on the firstcolor original value, the second color original value and the thirdcolor original value to obtain the first color correction value(FFC1_R1), the second color correction value (FFC1_G1), and the thirdcolor correction value (FFC1_B1), and the processor 110 executes thefollowing equations (19) to (21) to determine whether the currentsensing environment is a strong light environment. The processor 110 maydivide the first color correction value (FFC1_R1) by the second colorcorrection value (FFC1_G1) to obtain a seventh calculation value, anddetermine whether the seventh calculation value is greater than or equalto 1.2. The processor 110 may divide the third color correction value(FFC1_B1) by the second color correction value (FFC1_G1) to obtain aneighth calculation value, and determine whether the eighth calculationvalue is greater than or equal to 1. The processor 110 may divide thefirst color correction value (FFC1_R1) by the third color correctionvalue (FFC1_B1) to obtain a ninth calculation value, and determinewhether the ninth calculation value is greater than or equal to 1. Inthis aspect, if equation (19) to equation (21) are all satisfied, stepS420 is executed. If at least one of the equation (19) to the equation(21) is not satisfied, step S430 is executed.

$\begin{matrix}{\frac{FFC1\_ R1}{FFC1\_ G1} \geq 1.2} & {{Equation}(19)} \\{\frac{FFC1\_ B1}{FFC1\_ G1} \geq 1} & {{Equation}(20)} \\{\frac{FFC1\_ R1}{FFC1\_ B1} \geq 1} & {{Equation}(21)}\end{matrix}$

In step S430, the processor 110 may determine whether the illuminationlight for illuminating the target object is warm color light. It isworth noting that the warm color light may be caused by the illuminationlight provided by the display device or other light source elements, andthe illumination light is brighter compared with the light beforefingerprint sensing or because a red screen picture is displayed.However, the disclosure is not limited thereto. In this aspect, theprocessor 110 may first perform the first FFC on the first colororiginal value, the second color original value and the third colororiginal value to obtain the first color correction value (FFC1_R1), thesecond color correction value (FFC1_G1) and the third color correctionvalue (FFC1_B1). Moreover, the processor 110 executes the followingequation (22) to determine whether the illumination light forilluminating the target object is warm color light. In this embodiment,the processor 110 may compare whether the first color correction value(FFC1_R1) is greater than the second color correction value (FFC1_G1),and whether the second color correction value (FFC1_G1) is greater thanthe third color correction value (FFC1_B1). In this aspect, if theequation (22) is established, step S420 is executed. If the equation(22) is not established, step S440 is executed.

FFC1_R1>FFC1_G1>FFC1_B1  Equation (22)

In step S420, the processor 110 determines that the result of thecurrent sensing environment is an exception (i.e., the current sensingenvironment is a strong light environment or the current illuminationlight is a warm color light). The processor 110 may perform a second FFCon the first color original value, the second color original value andthe third color original value, and again determine whether the targetobject is a real finger or a fake finger. In this embodiment, theprocessor 110 may first perform the second FFC on the first colororiginal value, the second color original value and the third colororiginal value to obtain the first color correction value (FFC2_R1), thesecond color correction value (FFC2_G1) and the third color correctionvalue (FFC2_B1), and the processor 110 makes judgment with the abovepreset condition based on the numerical result of the second FFC todetermine again whether the target object is a real finger or a fakefinger. In an embodiment, the processor 110 may further provide relevantjudgment information to the central processing unit of the electronicdevice, so that the central processing unit of the electronic device canperform other related functions or processing accordingly, but thedisclosure is not limited thereto. In step S440, the processor 110determines that the result of the current sensing environment is not anexceptional case, so as to determine that the target object is a fakefinger.

It should be noted that, in an embodiment, the processor 110 may furtherperform calculation and analysis to determine the current sensingenvironment as described above based on the sensing results of therespective first color pixel, second color pixel and third color pixelof the pixel groups 211_1 to 211_N in the pixel array 200, and makestatistical calculation on the multiple determining results of the pixelgroups 211_1 to 211_N. In this aspect, when the plurality of determiningresults of the pixel groups 211_1 to 211_N are that the number ofdetermining results of strong light environment is greater than thesecond predetermined determining threshold, the final determining resultis output that the current environment is a strong light environment.When the multiple determining results of the pixel groups 211_1 to 211_Nare that the number of the determining results of the warm color lightis greater than the third preset determining threshold, the output finaldetermining result is that the current illumination light is the warmcolor light. On the contrary, it is determined that the target object isa fake finger.

FIG. 5 is a schematic circuit diagram of an under-screen fingerprintsensing device according to another embodiment of the presentdisclosure. Referring to FIG. 5, the under-screen fingerprint sensingdevice 500 includes a processor 510, a fingerprint sensor 520 and astorage device 530. The processor 510 is coupled to the fingerprintsensor 520 and the storage device 530. In this embodiment, theunder-screen fingerprint sensing device 500 is adaptable for anelectronic device (or terminal device) having a display device. It isworth noting that the relevant hardware features and implementation ofthe under-screen fingerprint sensing device 500 of this embodiment canbe derived from the descriptions of the above-mentioned embodiments inFIG. 1 to FIG. 4. The under-screen fingerprint sensing device 500 ofthis embodiment may include all the technical features of theunder-screen fingerprint sensing device 100 of the above-mentionedembodiment of FIG. 1. However, the storage device 530 of theunder-screen fingerprint sensing device 500 of this embodiment mayfurther store a determining module 531, a first database 532 and asecond database 533. In this embodiment, the determining module 531 is amachine learning (ML) module, and may include, for example, a k-nearestneighbors (KNN) algorithm and/or a rule-based algorithm.

In this embodiment, the first database 532 may include a plurality offake hand (finger) categories, and the second database 533 may include aplurality of real hand (finger) categories. The plurality of fake handcategories and the plurality of real hand categories may correspond todifferent combinations of the first color reference value, the secondcolor reference value, and the third color reference value,respectively.

In this embodiment, these fake hand categories may, for example, includeat least one corresponding to different object background colors,different color temperatures, fake fingerprint colors, or different fakehand materials in the following table 1.

TABLE 1 Fake hand Object Fake Different (finger) Screen color backgroundfingerprint fake hand categories temperatures colors colors materialsfake finger 1 Warm color Orange Black Color paper fake finger 2 Warmcolor Red Black Color paper fake finger 3 Warm color Yellow Black Colorpaper fake finger 4 Warm color Brown Black Color paper fake finger 5Warm color Pink Black Color paper fake finger 6 cool color Blue RedColor paper fake finger 7 cool color Green Black Color paper fake finger8 cool color Purpose Black Color paper fake finger 9 Other White RedColor paper fake finger 10 Other Black Black Color paper fake finger 11Other Dark gray Black Color card fake finger 12 Other Light gray BlackColor card fake finger 13 Other Bright red Black Color card fake finger14 Other Dard red Black Color card fake finger 15 Other High-grade BlackColor card gray

In this embodiment, these real hand categories may, for example, includeat least one corresponding to different finger pressing forces,different finger coverage areas, different finger sensing environmentsor different finger states in the following Table 2.

TABLE 2 Real hand finger (finger) coverage finger sensing categoriesFinger pressing force areas environment Real finger 1 Normal pressingforce 100% Normal indoor environment Real finger 2 Normal pressing force 50% Normal indoor environment Real finger 3 Normal pressing force 100%Dark room Real finger 4 Normal pressing force  50% Dark room Real finger5 Low pressing force 100% Normal indoor environment Real finger 6 Lowpressing force  50% Normal indoor environment Real finger 7 Low pressingforce 100% Dark room Real finger 8 Low pressing force  50% Dark roomReal finger 9 High pressing force 100% Normal indoor environment Realfinger 10 High pressing force  50% Normal indoor environment Real finger11 High pressing force 100% Dark room Real finger 12 High pressing force 50% Dark room Real finger 13 Normal pressing force 100% Strong lightenvironment Real finger 14 Normal pressing force  50% Strong lightenvironment Real finger 15 wet finger 100% Dark room Real finger 16 wetfinger  50% Dark room Real finger 17 wet finger 100% Normal indoorenvironment Real finger 18 wet finger  50% Normal indoor environmentReal finger 19 Dirty finger 100% Dark room Real finger 20 Clean finger 50% Dark room Real finger 21 Low light (20%) 100% Normal indoorenvironment Real finger 22 Low light (20%)  50% Normal indoorenvironment Real finger 23 Dimmed strong light 100% Strong light (20Klux) environment Real finger 24 Dimmed strong light  50% Strong light(20K lux) environment

FIG. 6 is a flowchart of a fingerprint sensing method according to asecond embodiment of the present disclosure. Referring to FIG. 5 andFIG. 6, the under-screen fingerprint sensing device 500 can perform thefollowing steps S610 to S630 to realize the anti-counterfeitingfunction. In step S610, when the fingerprint sensor 520 senses thetarget object, a plurality of pixel groups of the pixel array of thefingerprint sensor 520 (for example, a plurality of first color pixels211R_1 to 211R_N, a plurality of second color pixels 211G_1 to 211G_Nand a plurality of third color pixels 211B_1 to 211B_N of the pixelgroups 211_1 to 211_N of the pixel array 200 of FIG. 2) are usedrespectively to output a plurality of first color original values (suchas R1 to RN), a plurality of second color original values (such as G1 toGN) and a plurality of third color original values (such as B1 to BN)).In step S620, the processor 510 may perform FFC on the first colororiginal values (e.g., R1 to RN), the second color original values(e.g., G1 to GN), and the third color original values (e.g., B1 to BN),respectively, to generate a plurality of first color original values, aplurality of second color correction values, and a plurality of thirdcolor correction values. In step S630, the processor 510 may input thefirst color correction values, the second color correction values andthe third color correction values to the determining module 531, so asto be compared with at least one of the first database 532 and thesecond database 533 to determine whether the target object is a realfinger. Therefore, the under-screen fingerprint sensing device 500 andthe fingerprint sensing method of this embodiment can realize thefunction of judging whether the target object is a real finger.

In the aforementioned step S620, the processor 510 may perform the firstFFC as expressed in equation (1) to equation (3) on the plurality offirst color original values (e.g., R1 to RN), plurality of second colororiginal values (e.g., G1 to GN), and plurality of third color originalvalues (e.g., B1 to BN) respectively, to generate a plurality of firstcolor correction values (e.g., FFC1_R1 to FFC1_RN), a plurality ofsecond color correction values (e.g., FFC1_G1 to FFC1_GN) and aplurality of third color correction values (e.g., FFC1_B1 to FFC1_BN).Alternatively, in an embodiment, the processor 510 may perform thesecond FFC as expressed in the equation (4) to equation (6) on aplurality of first color original values (for example, R1 to RN), aplurality of second color original values (for example, G1 to GN), and aplurality of third color original values (for example, B1 to BN),respectively, to generate a plurality of first color correction values(e.g., FFC2_R1 to FFC2_RN), a plurality of second color correctionvalues (e.g., FFC2_G1 to FFC2_GN) and a plurality of third colorcorrection values (e.g., FFC2_B1 to FFC2_BN).

In the aforementioned step S630, the processor 510 may execute the KNNalgorithm in the determining module 531 to determine whether the targetobject is a real finger according to the classification result of thefirst color correction values, the second color correction values andthe third color correction values corresponding to at least one of thefirst database 532 and the second database 533 and output through theKNN algorithm. In this aspect, the processor 510 may execute the KNNalgorithm in the determining module 531 to determine the first colorcorrection values, the second color correction values and the thirdcolor correction values are the closest to which one of the plurality ofreal and fake hand classification results in at least one of the firstdatabase 532 and the second database 533, and the determining module 531can directly output the determining result.

Alternatively, the processor 510 may execute the rule-based algorithm inthe determining module 531 to perform counting on a plurality ofreal-hand scores that are output from the first color correction values,the second color correction values, and the third color correctionvalues through the rule-based algorithm and corresponding to at leastone of the first database 532 and the second database 533, to determinewhether the target object is a real finger. In this aspect, theprocessor 510 may determine whether the plurality of real-hand scoresexceeds a preset score threshold, and count the number of real-handscores exceeding the preset score threshold. Next, the processor 510 maydetermine whether the number of real-hand scores exceeding the presetscore threshold is greater than the preset number threshold to determinethe final determining result of the real and fake fingers. If the numberof real-hand scores exceeding the preset score threshold is greater thanthe preset number threshold, the processor 510 determines that thetarget object is a real finger. Conversely, if the number of real-handscores exceeding the preset score threshold is less than or equal to thepreset number threshold, the processor 510 determines that the targetobject is a fake finger. The processor 510 may execute the rule-basedalgorithm in the determining module 531 to classify the first colorcorrection values, the second color correction values and the thirdcolor correction values into a plurality of real and fake handclassification results in at least one of the first database 532 and thesecond database 533, and the determining module 531 can directly outputthe determining result according to the one with the largest count valueamong the real and fake hand classification results.

FIG. 7 is a flowchart of a fingerprint sensing method according to athird embodiment of the present disclosure. Referring to FIG. 5 and FIG.7, the under-screen fingerprint sensing device 500 may perform thefollowing steps S710 to S780 to implement the anti-counterfeitingfunction. In step S710, the under-screen fingerprint sensing device 500can sense the target object through the fingerprint sensor 520, so thatthe first color pixel, the second color pixel, and the third color pixelof the pixel array (such as the pixel array 200 in FIG. 2) of thefingerprint sensor 520 output the first color original value (R1), thesecond color original value (G1), and the third color original value(B1), respectively. In step S720, the processor 510 may perform a firstFFC on the first color original value (R1), the second color originalvalue (G1), and the third color original value (B1), respectively, togenerate a first color correction value (FFC1_R1), the second colorcorrection value (FFC1_G1), and the third color correction value(FFC1_B1). In this embodiment, the processor 510 may perform the firstFFC as expressed in the above equation (1) to equation (3). In stepS730, the processor 510 may determine whether the current sensingenvironment is a strong light environment according to the first colorcorrection value (FFC1_R1), the second color correction value (FFC1_G1)and the third color correction value (FFC1_B1). In this embodiment, theprocessor 510 can perform the calculations as expressed in the aboveequation (19) to equation (21) to determine whether the current sensingenvironment is a strong light environment.

In an embodiment, a plurality of pixel groups of the pixel array of thefingerprint sensor 520 can output a plurality of first color originalvalues, a plurality of second color original values, and a plurality ofthird color original values, respectively, and the processor 510performs a first FFC on the first color original values, the secondcolor original values, and the third color original values,respectively, to generate a plurality of first color correction values,a plurality of second color correction values, and a plurality of thirdcolor correction values. The processor 510 can execute the KNN algorithmin the determining module 531 to determine whether the current sensingenvironment is a strong light environment (e.g., the finger sensingenvironments of real fingers 13, 14, 23, and 24 in Table 2) according tothe classification results of the first color correction values, thesecond color correction values and the third color correction valuesthat are output through the KNN algorithm and corresponding to thesecond database 533. Alternatively, the processor 510 may also executethe rule-based algorithm in the determining module 531 to performcounting on a plurality of strong light environment scores that areoutput from the first color correction values, the second colorcorrection values, and the third color correction values through therule-based algorithm and corresponding to the second database 533, todetermine whether the current sensing environment is a strong lightenvironment (for example, the finger sensing environment of real fingers13, 14, 23, and 24 in Table 2).

If yes, the processor 510 executes step S740. If not, the processor 510executes step S760. In step S740, the processor 510 may determinewhether the target object is a real finger according to the first colorcorrection value (FFC1_R1), the second color correction value (FFC1_G1)and the third color correction value (FFC1_R1). In this embodiment, theprocessor 510 may perform the calculation as expressed in the aboveequation (7) to equation (9) to determine whether the target object is areal finger. Alternatively, in an embodiment, multiple pixel groups ofthe pixel array of the fingerprint sensor 520 may output a plurality offirst color original values, a plurality of second color originalvalues, and a plurality of third color original values, respectively,and processor 510 performs a first FFC on the first color originalvalues, the second color original values, and the third color originalvalues, respectively, to generate a plurality of first color correctionvalues, a plurality of second color correction values, and a pluralityof first color correction values. The processor 510 may perform stepS630 in the above-mentioned embodiment of FIG. 6 on the first colorcorrection values, the second color correction values and the thirdcolor correction values to determine whether the target object is a realfinger. If yes, in step S750, the processor 510 determines that thetarget object is a real finger, and the processor 510 or the centralprocessing unit of the electronic device can perform subsequentfingerprint analysis on the current fingerprint image. If not, in stepS780, the processor 510 determines that the target object is a fakefinger.

In step S760, the processor 510 may perform a second FFC on the firstcolor original value (R1), the second color original value (G1), and thethird color original value (B1) to generate the fourth color correctionvalue (FFC2_R1), the fifth color correction value (FFC2_G1), and thesixth color correction value (FFC2_B1). In this embodiment, theprocessor 510 may perform the second FFC as expressed in the aboveequation (4) to equation (6).

In step S770, the processor 510 may determine whether the target objectis a real finger according to the fourth color correction value(FFC2_R1), the fifth color correction value (FFC2_G1) and the sixthcolor correction value (FFC2_B1). In this embodiment, the processor 510may perform the calculation as expressed in the above equation (10) toequation (12) to determine whether the target object is a real finger.Alternatively, in an embodiment, multiple pixel groups of the pixelarray of the fingerprint sensor 520 may output the plurality of firstcolor original values, plurality of second color original values, andplurality of third color original values, respectively, and processor510 performs a second FFC on the first color original values, the secondcolor original values, and the third color original values,respectively, to generate the plurality of fourth color correctionvalues, plurality of fifth color correction values, and plurality ofsixth color correction values. The processor 510 may perform step S630in the above-mentioned embodiment of FIG. 6 on the fourth colorcorrection values, the fifth color correction values and the sixth colorcorrection values to determine whether the target object is a realfinger. If yes, in step S750, the processor 510 determines that thetarget object is a real finger, and the processor 510 or the centralprocessing unit of the electronic device can perform subsequentfingerprint analysis on the current fingerprint image. If not, in stepS780, the processor 510 determines that the target object is a fakefinger. Therefore, the under-screen fingerprint sensing device 500 andthe fingerprint sensing method of this embodiment can realize thefunction of judging whether the target object is a real finger.

FIG. 8 is a flowchart of a fingerprint sensing method according to afourth embodiment of the present disclosure. Referring to FIG. 5 andFIG. 8, the under-screen fingerprint sensing device 500 can perform thefollowing steps S810 to S870 to implement the anti-counterfeitingfunction. In step S810, the under-screen fingerprint sensing device 500can sense the target object through the fingerprint sensor 520, so thatthe first color pixel, the second color pixel and the second color pixelof the pixel array (such as the pixel array 200 in FIG. 2) of thefingerprint sensor 520 respectively output the first color originalvalue (R1), the second color original value (G1), and the third colororiginal value (B1), respectively. In step S820, the processor 510 mayperform the first FFC on the first color original value (R1), the secondcolor original value (G1), and the third color original value (B1),respectively, to generate the first color correction value (FFC1_R1),the second color correction value (FFC1_G1), and the third colorcorrection value (FFC1_B1). In this embodiment, the processor 510 mayperform the first FFC as expressed in the above equation (1) to equation(3).

In step S830, the processor 510 may determine whether the target objectis a real finger according to the first color correction value(FFC1_R1), the second color correction value (FFC1_G1) and the thirdcolor correction value (FFC1_B1). In this embodiment, the processor 510can perform calculation as expressed in the above equation (7) toequation (9) to determine whether the target object is a real finger.Alternatively, in an embodiment, multiple pixel groups of the pixelarray of the fingerprint sensor 520 may output the plurality of firstcolor original values, the plurality of second color original values,and the plurality of third color original values, respectively, andprocessor 510 performs a first FFC on the first color original values,the second color original values, and the third color original values,respectively, to generate a plurality of first color correction values,a plurality of second color correction values, and a plurality of thirdcolor correction values. The processor 510 may perform step S630 in theabove-mentioned embodiment of FIG. 6 on the first color correctionvalues, the second color correction values and the third colorcorrection values to determine whether the target object is a realfinger. If yes, in step S840, the processor 510 determines that thetarget object is a real finger, and the processor 510 or the centralprocessing unit of the electronic device can perform subsequentfingerprint analysis on the current fingerprint image. If not, theprocessor 510 executes step S850.

In step S850, the processor 510 may perform a second FFC on the firstcolor original value (R1), the second color original value (G1), and thethird color original value (B1) to generate the fourth color correctionvalue (FFC2_R1), the fifth color correction value (FFC2_G1), and thesixth color correction value (FFC2_B1). In this embodiment, theprocessor 510 may perform the second FFC as expressed in the aboveequation (4) to equation (6).

In step S860, the processor 510 may determine whether the target objectis a real finger according to the fourth color correction value(FFC2_R1), the fifth color correction value (FFC2_G1) and the sixthcolor correction value (FFC2_B1). In this embodiment, the processor 510may perform calculation as expressed in the above equation (10) toequation (12) to determine whether the target object is a real finger.Alternatively, in an embodiment, multiple pixel groups of the pixelarray of the fingerprint sensor 520 may respectively output theplurality of first color original values, the plurality of second colororiginal values, and the plurality of third color original values,respectively, and the processor 510 performs a second FFC on the firstcolor original values, the second color original values, and the thirdcolor original values, respectively, to generate the plurality of fourthcolor correction values, the plurality of fifth color correction values,and the plurality of sixth color correction values. The processor 510may perform step S630 in the above-mentioned embodiment of FIG. 6 on thefourth color correction values, the fifth color correction values andthe sixth color correction values to determine whether the target objectis a real finger. If yes, in step S840, the processor 510 determinesthat the target object is a real finger, and the processor 510 or thecentral processing unit of the electronic device can perform subsequentfingerprint analysis on the current fingerprint image. If not, in stepS850, the processor 510 determines that the target object is a fakefinger, so as to stop using the current fingerprint image for subsequentfingerprint analysis. Therefore, the under-screen fingerprint sensingdevice 500 and the fingerprint sensing method of this embodiment canrealize the function of judging whether the target object is a realfinger.

In addition, in another embodiment, when the processor 510 determinesthat the target object is a real finger in step S840, the processor 510may further input the first color correction value, the second colorcorrection value and the third color correction value to the determiningmodule 531, or input the fourth color correction value, the fifth colorcorrection value and the sixth color correction value to the determiningmodule 531, so as to be compared with the second database 533 to judgethe state of the target obj ect. The comparison method may be, forexample, an analysis method in which the processor 510 executes the KNNalgorithm in the determining module 531 described in step S630 in theembodiment of FIG. 6 or an analysis method in the rule-based algorithmin the determining module 531. In this aspect, the state of the targetobject may be, for example, a determining result of at least one of thereal hand (finger) classification, the finger pressing condition, thefinger coverage area, and the finger sensing environment as shown inTable 2 above. The processor 510 may use the information on the state ofthe target object in subsequent fingerprint identification, fingerprintimage processing or other application programs.

To sum up, the under-screen fingerprint sensing device and fingerprintsensing method of the present disclosure can use one of two FFCs tocorrect a plurality of color original values obtained by the fingerprintsensor, so as to effectively determine whether the currently sensedtarget object is a fake finger or a real finger. In addition, the meansfor judging real and fake fingers adopted by the under-screenfingerprint sensing device and fingerprint sensing method of the presentdisclosure may further be realized through numerical analysis andmachine learning, so that the under-screen fingerprint sensing devicecan provide an anti-counterfeiting function with high degree ofaccuracy.

Although the present disclosure has been disclosed above withembodiments, it is not intended to limit the present disclosure. Anyonewith ordinary knowledge in the technical field can make some changes andmodifications without departing from the spirit and scope of the presentdisclosure. Therefore, the scope to be protected by the presentdisclosure shall be subjected to the scope of the appended claims.

What is claimed is:
 1. An under-screen fingerprint sensing device,adaptable for an electronic equipment with a display device, comprising:a fingerprint sensor, disposed under the display device, and thefingerprint sensor having a pixel array, wherein a plurality of pixelgroups of the pixel array have a plurality of first color pixels, aplurality of second color pixels and a plurality of third color pixels,when the fingerprint sensor senses a target object, the first colorpixels, the second color pixels and the third color pixels of the pixelgroups respectively output a plurality of first color original values, aplurality of second color original values and a plurality of third colororiginal values; and a processor, coupled to the pixel array, whereinthe processor performs a flat-filed correction (FFC) on the first colororiginal values, the second color original values and the third colororiginal values respectively to generate a plurality of first colorcorrection values, a plurality of second color correction values and aplurality of third color correction values, wherein the processor inputsthe first color correction values, the second color correction valuesand the third color correction values into a determining module so as tobe compared with at least one of a first database and a second database,to determine whether the target object is a real finger.
 2. Theunder-screen fingerprint sensing device according to claim 1, whereinthe first database comprises a plurality of fake hand categories, andthe second database comprises a plurality of real hand categories,wherein the fake hand categories and the real hand categoriesrespectively correspond to different combinations of a first colorreference value, a second color reference value and a third colorreference value.
 3. The under-screen fingerprint sensing deviceaccording to claim 2, wherein the fake hand categories correspond to atleast one of different finger colors, different color temperatures, ordifferent fake hand materials.
 4. The under-screen fingerprint sensingdevice according to claim 2, wherein the real hand categories correspondto at least one of different finger pressing forces, different fingercoverage areas, different finger sensing environments or differentfinger states.
 5. The under-screen fingerprint sensing device accordingto claim 2, wherein the determining module comprises a K-nearestneighbors (KNN) algorithm, and the processor determines whether thetarget object is the real finger according to a classification result ofthe first color correction values, the second color correction valuesand the third color correction values corresponding to at least one ofthe first database and the second database and output through the KNNalgorithm.
 6. The under-screen fingerprint sensing device according toclaim 2, wherein the determining module comprises a rule-basedalgorithm, and the processor determines whether the target object is thereal finger according to a counting result of the first color correctionvalues, the second color correction values and the third colorcorrection values corresponding to at least one of the first databaseand the second database and output through the rule-based algorithm. 7.The under-screen fingerprint sensing device according to claim 1,wherein the FFC comprises: the processor performing subtraction on thefirst color original values and a first low reference value respectivelyto obtain a plurality of first calculation values, and the processorperforming subtraction on a first high reference value and the first lowreference value to obtain a second calculation value, wherein theprocessor divides the first calculation values by the second calculationvalue respectively to obtain the first color correction values, theprocessor performing subtraction on the second color original values anda second low reference value respectively to obtain a plurality of thirdcalculation values, and the processor performing subtraction on a secondhigh reference value and the second low reference value to obtain afourth calculation value, wherein the processor divides the thirdcalculation values by the fourth calculation value respectively toobtain the second color correction values, the processor performingsubtraction on the third color original values and a third low referencevalue respectively to obtain a plurality of fifth calculation values,and the processor performing subtraction on a third high reference valueand the third low reference value to obtain a sixth calculation value,wherein the processor divides the fifth calculation values by the sixthcalculation value respectively to obtain the third color correctionvalues.
 8. The under-screen fingerprint sensing device according toclaim 7, wherein the first high reference value, the second highreference value and the third high reference value are three first ADCvalues respectively corresponding to a first color, a second color and athird color and generated after the fingerprint sensor senses a standardwhite object.
 9. The under-screen fingerprint sensing device accordingto claim 7, wherein the first high reference value, the second highreference value and the third high reference value are another threefirst ADC values respectively corresponding to a first color, a secondcolor and a third color and generated after the fingerprint sensorsenses a standard skin-colored object.
 10. The under-screen fingerprintsensing device according to claim 7, wherein the first low referencevalue, the second low reference value and the third low reference valueare three second ADC values respectively corresponding to a first color,a second color and a third color and generated after the fingerprintsensor senses a standard black object.
 11. The under-screen fingerprintsensing device according to claim 1, wherein the first color pixels, thesecond color pixels and the third color pixels are respectively aplurality of red sensing pixels, a plurality of green sensing pixels anda plurality of blue sensing pixels.
 12. The under-screen fingerprintsensing device according to claim 1, wherein the first color pixels, thesecond color pixels and the third color pixels respectively comprise aplurality of red color filters, a plurality of green color filters and aplurality of blue color filters.
 13. A fingerprint sensing method,comprising: when a fingerprint sensor senses a target object, aplurality of first color pixels, a plurality of second color pixels, anda plurality of third color pixels of a plurality of pixel groups of apixel array of the fingerprint sensor are respectively used to output aplurality of first color original values, a plurality of second colororiginal values and a plurality of third color original values;performing an FFC on the first color original values, the second colororiginal values, and the third color original values, respectively, togenerate a plurality of first color correction values, a plurality ofsecond color correction values, and a plurality of third colorcorrection values; and inputting the first color correction values, thesecond color correction values and the third color correction valuesinto a determining module so as to be compared with at least one of afirst database and a second database, to determine whether the targetobject is a real finger.
 14. The fingerprint sensing method according toclaim 13, wherein the first database comprises a plurality of fake handcategories, and the second database comprises a plurality of real handcategories, wherein the fake hand categories and the real handcategories respectively correspond to different combinations of a firstcolor reference value, a second color reference value and a third colorreference value.
 15. The fingerprint sensing method according to claim14, wherein the fake hand categories correspond to at least one ofdifferent finger colors, different color temperatures, or different fakehand materials.
 16. The fingerprint sensing method according to claim14, wherein the real hand categories correspond to at least one ofdifferent finger pressing forces, different finger coverage areas,different finger sensing environments or different finger states. 17.The fingerprint sensing method according to claim 14, wherein thedetermining module comprises a K-nearest neighbors (KNN) algorithm, andthe step of determining whether target object is the real fingercomprises: determining whether the target object is the real fingeraccording to a classification result of the first color correctionvalues, the second color correction values and the third colorcorrection values corresponding to at least one of the first databaseand the second database and output through the KNN algorithm.
 18. Thefingerprint sensing method according to claim 14, wherein thedetermining module comprises a rule-based algorithm, and the step ofdetermining whether target object is the real finger comprises:determining whether the target object is the real finger according to acounting result of the first color correction values, the second colorcorrection values and the third color correction values corresponding toat least one of the first database and the second database and outputthrough the rule-based algorithm.
 19. The fingerprint sensing methodaccording to claim 13, wherein the FFC comprises: performing subtractionon the first color original values and a first low reference valuerespectively to obtain a plurality of first calculation values, andperforming subtraction on a first high reference value and the first lowreference value to obtain a second calculation value, wherein the firstcalculation values are divided by the second calculation valuerespectively to obtain the first color correction values; performingsubtraction on the second color original values and a second lowreference value respectively to obtain a plurality of third calculationvalues, and performing subtraction on a second high reference value andthe second low reference value to obtain a fourth calculation value,wherein the third calculation values are divided by the fourthcalculation value respectively to obtain the second color correctionvalues; and performing subtraction on the third color original valuesand a third low reference value respectively to obtain a plurality offifth calculation values, and performing subtraction on a third highreference value and the third low reference value to obtain a sixthcalculation value, wherein the fifth calculation values are divided bythe sixth calculation value respectively to obtain the third colorcorrection values.
 20. The fingerprint sensing method according to claim19, wherein the first high reference value, the second high referencevalue and the third high reference value are three first ADC valuesrespectively corresponding to a first color, a second color and a thirdcolor and generated after the fingerprint sensor senses a standard whiteobject.
 21. The fingerprint sensing method according to claim 19,wherein the first high reference value, the second high reference valueand the third high reference value are another three first ADC valuesrespectively corresponding to a first color, a second color and a thirdcolor and generated after the fingerprint sensor senses a standardskin-colored object.
 22. The fingerprint sensing method according toclaim 19, wherein the first low reference value, the second lowreference value and the third low reference value are three second ADCvalues respectively corresponding to a first color, a second color and athird color and generated after the fingerprint sensor senses a standardblack object.
 23. The fingerprint sensing method according to claim 13,wherein the first color pixels, the second color pixels and the thirdcolor pixels are respectively a plurality of red sensing pixels, aplurality of green sensing pixels and a plurality of blue sensingpixels.
 24. The fingerprint sensing method according to claim 13,wherein the first color pixels, the second color pixels and the thirdcolor pixels respectively comprise a plurality of red color filters, aplurality of green color filters and a plurality of blue color filters.